A Multi-Armed Bandit Approach to Distributed Robust Beamforming in Multicell Networks

This paper addresses the problem of maximizing the weighted signal-to-interference-plus-noise-ratio (SINR) targets at user terminals in a distributed manner in multicell interference networks. The optimization is constrained to strict individual base station (BS) transmit power limitations in the presence of imperfect channel state information (CSI). This problem is numerically intractable due to the coupling effect among a cluster of BSs operating under the same frequency bandwidth and robust constraints that involve the imperfect CSI. We first convert the original problem into a dual total transmit power minimization problem subject to a set of robust SINR constraints in the centralized worst-case scenario. Then the resulting global optimization problem is decomposed into a set of independent subproblems at individual BSs. Finally, a multi-arm bandit based algorithm is proposed to optimally scale the SINR targets in a distributed manner based on individual BS power budgets, and coordinate intercell interference among the BSs with a light inter-BS communication overhead. Simulation results demonstrate the advantage of the proposed scheme in terms of providing larger SINR operation range and robustness to the CSI uncertainties.